无迹信息滤波耦合交互式多模型的多传感器机器人轨迹控制

摘要

为了实现对包装运输过程中机器人的轨迹跟踪, 基于无迹信息滤波技术 (UIF) 和交互式多模型技术 (IMM), 提出了一种新的多传感器数据融合算法 (UIF-IMM), 融合了单个IMM滤波器、每个UIF的信息状态贡献和信息矩阵等信息.通过对机器人轨迹跟踪可知:在4种轨迹跟踪算法中, 提出的算法跟踪效果最好, 均方根位置误差和角度误差均最小, 分别为0.047和0.9.在分布式传感器节点 (UIF-IMM 2) 中, 采用模型似然函数组合的多传感器融合算法, 其位置精度和角度精度均优于不进行组合的多传感器融合算法 (UIF-IMM 1).提出的滤波方法可以很好地解决分布式多传感器环境下机器人的跟踪问题, 在机动目标定位领域具有一定的参考价值.%The work aims to track the robot in the process of packaging and transportation.A new method that combines an unscented information filtering (UIF) algorithm with an interacting multiple model (IMM) framework under a distributed multiple-sensor fusion architecture is proposed.The proposed algorithm fuses data, such as the information state contribution and information matrix, of each UIF that is included in an IMM filter.By comparing the tracking effect of four different algorithms, it is proved that the tracking algorithm proposed in this paper is the best.The root mean square position error and angle error were the smallest, with the value of 0.047 and 0.9 respectively.The multi sensor fusion algorithm used in the distributed sensor node (UIF-IMM2) combination of model likelihood function is better than the multi sensor fusion algorithm without combination (UIF-IMM1).The filtering method proposed in this paper can solve the tracking problem of packaging robot in distributed multi-sensor environment, which has certain reference value in the field of maneuvering target location.